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001     1007797
005     20250317091734.0
037 _ _ |a FZJ-2023-02192
100 1 _ |a Breuer, Thomas
|0 P:(DE-Juel1)138707
|b 0
|e Corresponding author
|u fzj
111 2 _ |a The International Conference for High Performance Computing, Networking, Storage, and Analysis
|g SC22
|c Dallas
|d 2022-11-13 - 2022-11-18
|w USA
245 _ _ |a Enabling energy systems research on HPC
260 _ _ |c 2022
|b SC22 Supercomputing conference
295 1 0 |a SC Technical Program Archives - Research posters
300 _ _ |a 3 pp.
336 7 _ |a CONFERENCE_PAPER
|2 ORCID
336 7 _ |a Conference Paper
|0 33
|2 EndNote
336 7 _ |a INPROCEEDINGS
|2 BibTeX
336 7 _ |a conferenceObject
|2 DRIVER
336 7 _ |a Output Types/Conference Paper
|2 DataCite
336 7 _ |a Contribution to a conference proceedings
|b contrib
|m contrib
|0 PUB:(DE-HGF)8
|s 1687163278_9014
|2 PUB:(DE-HGF)
336 7 _ |a Contribution to a book
|0 PUB:(DE-HGF)7
|2 PUB:(DE-HGF)
|m contb
520 _ _ |a Energy systems research strongly relies on large modeling frameworks. Many of them use linear optimization approaches to calculate blueprints for ideal future energy systems, which become increasingly complex, as do the models. The state of the art is to compute them with shared-memory computers combined with approaches to reduce the model size. We overcome this and implement a fully automated workflow on HPC using a newly developed solver for distributed memory architectures. Moreover, we address the challenge of uncertainty in scenario analysis by performing sophisticated parameter variations for large-scale power system models, which cannot be solved in the conventional way. Preliminary results show that we are able to identify clusters of future energy system designs, which perform well from different perspectives of energy system research and also consider disruptive events. Furthermore, we also observe that our approach provides the most insights when being applied to complex rather than simple models.
536 _ _ |a 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)
|0 G:(DE-HGF)POF4-5112
|c POF4-511
|f POF IV
|x 0
536 _ _ |a Verbundvorhaben: UNSEEN ' Bewertung der Unsicherheiten in linear optimierenden Energiesystem-Modellen unter Zuhilfenahme Neuronaler Netze, Teilvorhaben: Entwicklung einer integrierten HPC-Workflow Umgebung zur Kopplung von Optimierungsmethoden mit Methode (03EI1004F)
|0 G:(BMWi)03EI1004F
|c 03EI1004F
|x 1
536 _ _ |0 G:(DE-Juel-1)ATMLAO
|a ATMLAO - ATML Application Optimization and User Service Tools (ATMLAO)
|c ATMLAO
|x 2
700 1 _ |a Cao, Karl-Kiên
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Wetzel, Manuel
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Frey, Ulrich
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Sasanpour, Shima
|0 P:(DE-HGF)0
|b 4
700 1 _ |a Buschman, Jan
|0 P:(DE-HGF)0
|b 5
700 1 _ |a Böhme, Aileen
|0 P:(DE-HGF)0
|b 6
700 1 _ |a Vanaret, Charlie
|0 P:(DE-HGF)0
|b 7
856 4 _ |u https://sc22.supercomputing.org/proceedings/tech_poster/tech_poster_pages/rpost109.html
856 4 _ |u https://juser.fz-juelich.de/record/1007797/files/UNSEEN_SC_Poster_Summary.pdf
|y Restricted
909 C O |o oai:juser.fz-juelich.de:1007797
|p VDB
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)138707
913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
|1 G:(DE-HGF)POF4-510
|0 G:(DE-HGF)POF4-511
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Enabling Computational- & Data-Intensive Science and Engineering
|9 G:(DE-HGF)POF4-5112
|x 0
914 1 _ |y 2023
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 0
980 _ _ |a contrib
980 _ _ |a VDB
980 _ _ |a contb
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a UNRESTRICTED

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